We propose a new image and blur prior model, based on nonstationary autoregressive (AR) models, and use these to blindly deconvolve blurred photographic images, using the Gibbs sa...
Deformable models are an attractive approach to recognizing nonrigid objects which have considerable within class variability. However, there are severe search problems associated...
Christopher K. I. Williams, Michael Revow, Geoffre...
In this paper we address the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context standard motion estimation techniques ...
In this paper, we present a real-time image processing technique for the detection of steam in video images. The assumption made is that the presence of steam acts as a blurring p...
We present a new method for training deformable models. Assume that we have training images where part locations have been labeled. Typically, one fits a model by maximizing the l...